Communication devices such as wireless devices are also known as e.g. User Equipments (UE), mobile terminals, wireless terminals and/or Mobile Stations (MS). Wireless devices are enabled to communicate wirelessly in a cellular communications network or wireless communication network, sometimes also referred to as a cellular radio system, cellular system, or cellular network. The communication may be performed e.g. between two wireless devices, between a wireless device and a regular telephone and/or between a wireless device and a server via a Radio Access Network (RAN) and possibly one or more core networks, comprised within the wireless communications network.
Wireless devices may further be referred to as mobile telephones, cellular telephones, laptops, or tablets with wireless capability, just to mention some further examples. The wireless devices in the present context may be, for example, portable, pocket-storable, hand-held, computer-comprised, or vehicle-mounted mobile devices, enabled to communicate voice and/or data, via the RAN, with another entity, such as another terminal or a server.
The wireless communications network covers a geographical area which may be divided into cell areas, each cell area being served by an access node such as a Base Station (BS), e.g. a Radio Base Station (RBS), which sometimes may be referred to as e.g., evolved Node B (“eNB”), “eNodeB”, “NodeB”, “B node”, or BTS (Base Transceiver Station), depending on the technology and terminology used. The base stations may be of different classes such as e.g. Wide Area Base Stations, Medium Range Base Stations, Local Area Base Stations and Home Base Stations, based on transmission power and thereby also cell size. A cell is the geographical area where radio coverage is provided by the base station at a base station site. One base station, situated on the base station site, may serve one or several cells. Further, each base station may support one or several communication technologies. The wireless communications network may also be a non-cellular system, comprising network nodes which may serve receiving nodes, such as wireless devices, with serving beams. The base stations communicate over the air interface operating on radio frequencies with the terminals within range of the base stations. In the context of this disclosure, the expression Downlink (DL) is used for the transmission path from the base station to the wireless device. The expression Uplink (UL) is used for the transmission path in the opposite direction i.e. from the wireless device to the base station.
In 3rd Generation Partnership Project (3GPP)) Long Term Evolution (LTE), network nodes, which may be referred to as eNodeBs or even eNBs, may be directly connected to one or more core networks. All data transmission is in LTE controlled by the radio base station.
3GPP LTE radio access standard has been written in order to support high bitrates and low latency both for uplink and downlink traffic.
Multi-antenna techniques may significantly increase the data rates and reliability of a wireless communication system. The 5th Generation (5G) technology, which is currently being developed, incorporates the use of beamforming. Beamforming may be understood as a signal processing technique which relies on combining elements in an array antenna in such a way that signals at particular angles experience constructive interference while others experience destructive interference. The beams used may typically be highly directive and provide gains of 20 decibels (dB) or more since so many antenna elements may participate in forming a beam. An array antenna may consist of many antenna elements to achieve a large array gain. Many antenna elements may participate in forming a beam, and the beams are typically highly directive, giving beamforming gains of 20 decibels (dB) or more. Each Transmission Point (TP) may, by use of an array antenna, generate transmission of a large number of beams having different pointing direction and/or polarization. The transmission of a signal is performed over multiple antenna elements and applying individual complex weights to these antenna elements, such that the signal is basically intended for a single wireless device or terminal position. Precoding may be understood as a process by which incoming data may be distributed over each antenna port. Hence, precoding may be interpreted as multiplying a signal with different beamforming weights for each antenna port prior to transmission. A precoding vector contains the complex beamforming weights these antenna elements are to use for transmission. By applying precoding to all antennas, the base station may make constructive interference among signals at the locations of the intended terminals, and destructive almost everywhere else. Furthermore, as the number of antennas increases, the energy may be focused with extreme precision into small regions in space. The result is spatial selectivity, such that beamforming may be understood as a way to transmit a signal with such narrow beams that it is intended for a single wireless device or a group of wireless devices in a similar geographical position. In 5G systems, the number of antenna elements at the transmitter and/or receiver side may be significantly increased compared to common 3G and 4G systems.
Multi-antenna techniques may significantly increase the data rates and reliability of a wireless communication system. The performance is in particular improved if both the transmitter and the receiver are equipped with multiple antennas, which results in a multiple-input multiple-output (MIMO) communication channel. Such systems and/or related techniques are commonly referred to as MIMO.
The LTE standard is currently evolving with enhanced MIMO support. In the 5th Generation (5G) technology, which is currently being developed, massive Multiple-Input Multiple-Output (MIMO) is one of the best candidate technologies for the radio physical layer. Massive MIMO, which may also be known as large-scale antenna systems and very large MIMO, may be understood as a multi-user MIMO technology where each BS may be equipped with a large number of antenna elements, at least 50, which may be used to serve many terminals that share the same time and frequency band and are separated in the spatial domain.
Beamforming, as well as massive MIMO, may operate in Time Division Duplex (TDD) mode. In TDD mode, a single carrier frequency may be used for uplink and downlink transmissions, and uplink and downlink transmissions are separated in the time domain on a cell basis. In reciprocity based TDD systems, the link from a transmitter to a received may match the link from the receiver to the transmitter, such that the estimated channel at the transmitter may directly be used for adaptive signal processing. The channel impulse responses may be understood to be the same in both uplink and downlink, since uplink and downlink transmissions occur in the same carrier, Channel reciprocity may allow the BSs to acquire Channel State Information (CSI) from pilot sequences transmitted by the terminals in the uplink. This CSI may then be useful for both the uplink and the downlink, avoiding the need to rely on CSI reporting from the terminals themselves.
Reciprocity based Time Division Duplex (TDD) systems are of particular interest in a 5th Generation (5G) context, since massive MIMO may rely on them. Reciprocity based beamforming relies on accurate Channel State Information at the Transmitter (CSI-T). In case the number of transmit antennas is significantly larger than the number of receive antennas, as may be the case in a TDD massive MIMO downlink scenario, then the CSI-T may be efficiently obtained by transmission of Sounding Reference Signal (SRS) in the reverse link.
FIG. 1 is a schematic representation of the two steps of reciprocity based beamforming in a massive MIMO system. In step one, CSI acquisition at the BS via Sounding Reference Signal (SRS), the UEs send an uplink Sounding Reference Signal (SRS) and the base station measures on the SRS:s and calculates the beamforming parameters for each user. This is shown in the top figure. The second step, reciprocity based downlink and uplink beamforming, is shown in the bottom figure. In the second step, the beamforming weights obtained by the first step are used.
In the context of a massive MIMO, there are many more BS antennas than terminals; for example, twice as many, but ideally as many as possible. Massive MIMO may offer many benefits over conventional multi-user MIMO. First, conventional multi-user MIMO is not a scalable technology, since it has been designed to support systems with roughly equal numbers of service antennas and terminals, and relies on Frequency Division Duplex (FDD) operation. In the case of FDD operation, there may be two carrier frequencies, one for uplink transmission and one for downlink transmission. By contrast, in massive MIMO, with the large excess of service antennas over active terminals, TDD operation may bring huge improvements in throughput and radiated energy efficiency. On the one hand, these benefits result from the aggressive spatial multiplexing achieved by appropriately shaping the signals sent out and received by the base station antennas.
Other benefits of massive MIMO may include use of simple low-power components, since massive MIMO relies on simple signal processing techniques, reduced latency, and robustness against intentional jamming.
On the other hand, by operating in TDD mode, massive MIMO may exploit the channel reciprocity property.
By virtue of the law of large numbers, according to which the sum of a large number of random values in a sample approaches the mean value of the population, the effective scalar channel gain, that is the path gain including beam-forming gain, seen by each terminal is close to a deterministic constant. The fact that the effective channel gain is kept constant long term, is called channel hardening. Thanks to the channel hardening, the terminals may reliably decode the downlink data using only long-term statistical CSI, making most of the physical layer control signaling redundant, and therefore resulting in the so-called low-cost CSI acquisition. This renders the conventional resource allocation concepts unnecessary and results in a simplification of the Media Access Control (MAC) layer. These benefits have elevated massive MIMO to a central position in preliminary 5G discussions.
However, the performance of systems relying on CSI acquisition via channel reciprocity, such as TDD beamforming and massive MIMO, may be affected by some limiting factors. First, channel reciprocity requires hardware calibration. Second, a basic phenomenon which is so-called pilot contamination effect may profoundly limit the performance of massive MIMO systems. Theoretically, every terminal in a massive MIMO system may be assigned an orthogonal uplink pilot sequence. However, the maximum number of orthogonal pilot sequences that may exist is upper-bounded by the size of the coherence interval. The coherence interval may be understood as is the time-frequency interval in which a channel is more or less the same. The coherence interval is the product of the coherence time and coherence bandwidth, which may be understood as the amount of time and the frequency bandwidth, respectively, in which the channel is more or less the same. Hence, adopting orthogonal pilots leads to inefficient resource allocation as the number of the terminals increases or it is not physically possible to perform when the coherence interval is too short. As a consequence, pilots may need to be reused across cells, or even within the home cell, for higher cell density. This inevitably causes interference among terminals which share the same pilot. Pilot contamination does not vanish as the number of BS antennas grows large, and so it is the one impairment that remains asymptotically.
Additional limiting factors further compromise the performance of systems relying on channel reciprocity.